Papers with Code 아카이브

3D Reconstruction

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하위 태스크: 7
평가표: 10
보존된 평가 기록: 44

3D Reconstruction is the task of creating a 3D model or representation of an object or scene from 2D images or other data sources. The goal of 3D reconstruction is to create a virtual representation of an object or scene that can be used for a variety of purposes, such as visualization, animation, simulation, and analysis. It can be used in fields such as computer vision, robotics, and virtual reality.

Image: Gwak et al

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/EnVision-Research/Kiss3DGen

공식 코드

Kiss3DGen: Repurposing Image Diffusion Models for 3D Asset Generation

https://github.com/EnVision-Research/Ref-NeuS

공식 코드

Ref-NeuS: Ambiguity-Reduced Neural Implicit Surface Learning for Multi-View Reconstruction with Reflection

https://github.com/FangjinhuaWang/PatchmatchNet

공식 코드

PatchmatchNet: Learned Multi-View Patchmatch Stereo

https://github.com/Fangkang515/CE3D

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Chat-Edit-3D: Interactive 3D Scene Editing via Text Prompts

https://github.com/GAP-LAB-CUHK-SZ/deepFashion3D

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Deep Fashion3D: A Dataset and Benchmark for 3D Garment Reconstruction from Single Images

https://github.com/GATECH-EIC/Omni-Recon

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Omni-Recon: Harnessing Image-based Rendering for General-Purpose Neural Radiance Fields

https://github.com/GCVCG/VolETA-MetaFood

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MetaFood CVPR 2024 Challenge on Physically Informed 3D Food Reconstruction: Methods and Results

https://github.com/GaryZhu1996/GARNet

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GARNet: Global-Aware Multi-View 3D Reconstruction Network and the Cost-Performance Tradeoff

https://github.com/GradientSpaces/LivingScenes

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Living Scenes: Multi-object Relocalization and Reconstruction in Changing 3D Environments

https://github.com/GuidoManni/BodySLAM

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BodySLAM: A Generalized Monocular Visual SLAM Framework for Surgical Applications

https://github.com/HKUST-Aerial-Robotics/ESVO

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Event-based Stereo Visual Odometry

https://github.com/HongwenZhang/DaNet-DensePose2SMPL

공식 코드

Learning 3D Human Shape and Pose from Dense Body Parts

https://github.com/HuSTeP-Human-Speech-Text-Processing-Lab/XLSR-GRKAN-Conformer

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Pushing the Performance of Synthetic Speech Detection with Kolmogorov-Arnold Networks and Self-Supervised Learning Models

https://github.com/IDT-ITI/Adv-XAI-Deepfakes

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Improving the Perturbation-Based Explanation of Deepfake Detectors Through the Use of Adversarially-Generated Samples

https://github.com/IIT-PAVIS/ExHistCNN

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Where to Explore Next? ExHistCNN for History-aware Autonomous 3D Exploration

https://github.com/IRVLUTD/HO-Cap

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HO-Cap: A Capture System and Dataset for 3D Reconstruction and Pose Tracking of Hand-Object Interaction

https://github.com/IntelRealSense/librealsense

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Intel RealSense Stereoscopic Depth Cameras

https://github.com/Inter3D-ui/Inter3D

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Inter3D: A Benchmark and Strong Baseline for Human-Interactive 3D Object Reconstruction

https://github.com/JOY-MM/JoyGen

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JoyGen: Audio-Driven 3D Depth-Aware Talking-Face Video Editing

https://github.com/Jerrypiglet/ScaleNet

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Single View Metrology in the Wild

https://github.com/Jessegator/Audio_robustness_evaluation

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Measuring the Robustness of Audio Deepfake Detectors

https://github.com/Jiawei-Yao0812/NDCScene

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NDC-Scene: Boost Monocular 3D Semantic Scene Completion in Normalized Device Coordinates Space

https://github.com/JiayuYANG/CVP-MVSNet

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Cost Volume Pyramid Based Depth Inference for Multi-View Stereo

https://github.com/Jixuan-Fan/Momentum-GS

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Momentum-GS: Momentum Gaussian Self-Distillation for High-Quality Large Scene Reconstruction

https://github.com/JohannaXie/GauSS-MI

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GauSS-MI: Gaussian Splatting Shannon Mutual Information for Active 3D Reconstruction

https://github.com/Jumponthemoon/WeatherGS

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WeatherGS: 3D Scene Reconstruction in Adverse Weather Conditions via Gaussian Splatting

https://github.com/KU-CVLAB/3DGAN-Inversion

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3D GAN Inversion with Pose Optimization

https://github.com/KU-CVLAB/RAIN-GS

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Relaxing Accurate Initialization Constraint for 3D Gaussian Splatting

https://github.com/KU-CVLAB/SE-NeRF

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Self-Evolving Neural Radiance Fields

https://github.com/KamruzzamanAsif/BanglaFake

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BanglaFake: Constructing and Evaluating a Specialized Bengali Deepfake Audio Dataset

https://github.com/KarenUllrich/pytorch-backprojection

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Differentiable probabilistic models of scientific imaging with the Fourier slice theorem

https://github.com/Kayaba-Akihiko/3DDX

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3DDX: Bone Surface Reconstruction from a Single Standard-Geometry Radiograph via Dual-Face Depth Estimation

https://github.com/Kulbear/ivus-segmentation-icsm2018

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IVUS-Net: An Intravascular Ultrasound Segmentation Network

https://github.com/LIA-DiTella/DiffUDF

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DUDF: Differentiable Unsigned Distance Fields with Hyperbolic Scaling

https://github.com/LMescheder/Occupancy-Networks

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Occupancy Networks: Learning 3D Reconstruction in Function Space

https://github.com/Lakonik/SSDNeRF

공식 코드

Single-Stage Diffusion NeRF: A Unified Approach to 3D Generation and Reconstruction

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.